Department of Pathology and Laboratory Medicine, Tufts Medical Center, Boston, MA, USA.
Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA.
Virchows Arch. 2021 Sep;479(3):481-491. doi: 10.1007/s00428-021-03085-7. Epub 2021 Mar 17.
Primary gastrointestinal neuroendocrine carcinoma (GI-NEC) cannot be distinguished morphologically from pulmonary neuroendocrine carcinoma (P-NEC). This can present a significant diagnostic challenge in cases where site of origin cannot be readily determined. To identify immunohistochemical (IHC) markers that can be used to reliably distinguish between GI-NECs and P-NECs, we constructed 3-mm tissue microarrays, one containing 13 GI-NECs and one containing 20 P-NECs. IHC was performed on both microarrays using 21 stains: AE1/AE3, CK7, CK20, synaptophysin, chromogranin, CD56, INSM1, SSTR2A, CDX2, SATB2, TTF1, Napsin A, PR, GATA3, PAX8, ISL1, beta-catenin, AFP, SMAD4, Rb, and p53. For GI-NEC, the most strongly expressed marker was synaptophysin (mean H-score 248), while AE1/AE3 was the most strongly expressed in P-NEC (mean H-score 230), which was stronger than in GI-NEC (p = 0.011). Other markers that were stronger overall in P-NEC than in GI-NEC included CK7 (p < 0.0001) and TTF1 (p < 0.0001). Markers that were stronger overall in GI-NEC than in P-NEC included SSTR2A (p = 0.0021), SATB2 (p = 0.018), CDX2 (p = 0.019), and beta-catenin (nuclear; p = 0.029). SMAD4, Rb, and p53 showed similar rates of abnormal protein expression. Based on these results, a stepwise algorithmic approach utilizing CK7, TTF1, beta-catenin, CDX2, and SSTR2A had a 91% overall accuracy in distinguishing these GI-NEC from P-NEC. This was tested on a second cohort of 10 metastatic GI-NEC and 10 metastatic P-NEC, with an accuracy in this cohort of 85% and an overall accuracy of 89% for the 53 cases tested. Our algorithm reasonably discriminates GI-NEC from P-NEC using currently available IHC stains.
原发性胃肠道神经内分泌癌(GI-NEC)在形态上无法与肺神经内分泌癌(P-NEC)区分。在原发部位难以确定的情况下,这可能会带来重大的诊断挑战。为了确定可用于可靠区分 GI-NEC 和 P-NEC 的免疫组织化学(IHC)标志物,我们构建了 3 毫米组织微阵列,一个包含 13 个 GI-NEC,另一个包含 20 个 P-NEC。使用 21 种染色剂对两个微阵列进行了 IHC 染色:AE1/AE3、CK7、CK20、突触素、嗜铬粒蛋白、CD56、INSM1、SSTR2A、CDX2、SATB2、TTF1、Napsin A、PR、GATA3、PAX8、ISL1、β-连环蛋白、AFP、SMAD4、Rb 和 p53。对于 GI-NEC,表达最强的标志物是突触素(平均 H 评分 248),而 AE1/AE3 在 P-NEC 中的表达最强(平均 H 评分 230),强于 GI-NEC(p=0.011)。在 P-NEC 中总体表达强于 GI-NEC 的其他标志物包括 CK7(p<0.0001)和 TTF1(p<0.0001)。在 GI-NEC 中总体表达强于 P-NEC 的标志物包括 SSTR2A(p=0.0021)、SATB2(p=0.018)、CDX2(p=0.019)和β-连环蛋白(核;p=0.029)。SMAD4、Rb 和 p53 显示出相似的异常蛋白表达率。基于这些结果,利用 CK7、TTF1、β-连环蛋白、CDX2 和 SSTR2A 的逐步算法方法在区分这些 GI-NEC 和 P-NEC 方面具有 91%的总体准确性。该算法在第二个队列的 10 例转移性 GI-NEC 和 10 例转移性 P-NEC 中进行了测试,在该队列中的准确性为 85%,在测试的 53 例中总体准确性为 89%。我们的算法使用当前可用的 IHC 染色剂合理地区分 GI-NEC 和 P-NEC。